Segmentation-Based Measurement of Orbital Structures: Achievements in Eyeball Volume Estimation and Barriers in Optic Nerve Analysis
Despite these challenges, the study highlights the potential of deep learning-based segmentation to automate the assessment of ocular structures, particularly in measuring eyeball volume, while leaving room for further improvement in optic nerve analysis.
Authors
- Yong Oh Lee (ORCID: https://orcid.org/0000-0003-3817-3620)
- Jisun Paik (ORCID: https://orcid.org/0000-0001-5628-7723)
- Won-kyung Cho
- Yeon Woong Chung (ORCID: https://orcid.org/0000-0002-3072-9295)
- Hana Kim
- Jungyul Park (ORCID: https://orcid.org/0000-0002-8626-7384)
Institutions
- The Catholic University of Korea St. Vincent's Hospital (KR)
- The Catholic University of Korea Uijeongbu St. Mary's Hospital (KR)
- The Catholic University of Korea Yeouido St. Mary's Hospital (KR)
- The Catholic University of Korea Seoul St. Mary's Hospital (KR)
- Catholic University of Korea (KR)
- Hongik University (KR)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-11-23
- DOI
- https://doi.org/10.3390/diagnostics14232643
- Primary Topic
- Facial Trauma and Fracture Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea